AI Analytics Engineer (Business Analytics)

Airtable•Austin, TX

11h

About The Position

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. Join Airtable as an Analytics Engineer supporting our Strategic Finance and Accounting teams, where you’ll take an AI-first approach to building the next generation of analytics infrastructure and tooling. This is a unique opportunity to shape how Finance stakeholders access and leverage data, driving real-time, self-serve insights and accelerating the adoption of AI-native analytics across Airtable. In this role, you’ll own the canonical financial data models and analytics infrastructure that power critical metrics like ACV, ARR, billings, and revenue. You’ll build scalable data pipelines, dashboards, and AI-powered systems that enable Finance stakeholders to explore data independently and make confident decisions. If you’re passionate about data, finance, and emerging AI tooling—and want to help define how analytics evolves inside a modern software company—we’d love to meet you.

Requirements

Technically curious and AI-forward: You’re energized by LLMs, prompt engineering, and the evolving landscape of AI tooling. You’ve experimented with tools like Claude/Claude Code, ChatGPT, or Manus, and you’re eager to build systems around them, not just use them.
A builder at heart: You have a bias toward making things. Whether it’s a prototype, a pipeline, or a quick script to test an idea, you default to building rather than theorizing. You’re comfortable picking up new technical skills and exploring unfamiliar domains, especially with AI tooling accelerating what’s possible.
Analytically grounded: You’re SQL-proficient and have experience with modern data tools (dbt, Databricks, Snowflake, or similar). You have strong intuition for when data “looks wrong” and can validate query logic and troubleshoot issues independently.
Detail-oriented with financial rigor: You understand that financial data demands precision. You’re driven by curiosity to explore data beyond the surface, but you never sacrifice accuracy for speed.
A clear communicator and strong writer: Context engineering is fundamentally a writing discipline. You can translate complex business logic into precise, structured documentation that both humans and LLMs can interpret.
Business-minded: You’re genuinely curious about how the business works, how we sell, how revenue flows, what metrics matter and why. You ask “what decision does this support?” not just “is the SQL correct?”
Thrives in ambiguity: You proactively create clarity and forward momentum, even when requirements are incomplete or rapidly changing. You own workstreams end-to-end, from scoping the problem to iterating based on feedback.
Not married to legacy tooling: You’re more interested in what’s emerging than what’s established. You evaluate tools based on what they enable, not how long they’ve been around.

Responsibilities

Design and maintain trusted data models for core financial metrics including ACV, ARR, billings, revenue recognition, and cost allocation, managing the full lifecycle from prototyping through production
Develop and govern dbt data pipelines, establishing data integrity standards and SLAs that ensure timely and accurate delivery of financial data across Finance and Accounting
Build and optimize dashboards that deliver real-time, self-serve insights across key financial areas including revenue performance, expense tracking, budget variance, and forecasting accuracy
Enable data independence for Finance stakeholders by eliminating reliance on ad-hoc data requests and manual reporting, building scalable self-service datasets in Looker and Omni for the Finance team and broader company
Collaborate with Finance and data partners to establish the AI Business Context layer for financial use cases, translating accounting logic, metric definitions, and business rules into structured formats that AI tools can interpret accurately
Develop tools that enable natural language access to financial data and AI-assisted reporting, empowering non-technical Finance stakeholders to explore insights independently
Design and implement AI-powered workflows that automatically surface patterns, anomalies, and meaningful changes in financial data, delivering insights proactively to stakeholders
Serve as the primary data partner for FP&A, Accounting, and Finance leadership, supporting strategic financial analysis and decision-making aimed at growing the business.
Translate complex data insights into clear business recommendations through dashboards, memos, and presentations that drive action
Drive cross-functional adoption of analytics and AI tooling, partnering with Finance stakeholders to onboard users, answer questions, triage issues, and train teams on new capabilities
Develop deep expertise in Airtable’s financial data models, pipelines, and BI tools (dbt, Looker, Omni) within the first six months, becoming the go-to internal expert for Finance data